i3Capture is a Desktop .NET application that allows a user to electronically capture paper documents, optionally extract metadata from configured zones using OCR, ICR, MICR, OMR and Barcode recognition and create digital image files with associated metadata output file. The application utilizes three stages: Capture, Process and Output.
Allows users to scan single or batches of paper documents thereby digitizing large amounts of data.
This is an intermediate stage that enables image clean-up for improved quality control.
Image pages can be rescanned if not initially scanned properly. Options are also available to rescan, insert or append pages within an existing document.
Preprocessing actions can be applied to the entire page or to specified regions of interest as defined. Several preprocessing actions for image clean up are provided; including deskew, border removal, line removal, despeckle, mirror, flip, zoom, smooth, negate and many more.
Various functions like split, merge, cut, copy and paste can be performed on image pages to group them into documents.
Recognize machine-printed uppercase/lowercase alphabetic, numeric, accented characters, many currency symbols, digits, arithmetic symbols, expanded punctuation characters and more
Recognizes hand-printed American and European English characters using pre-defined character sets: uppercase, lowercase, mixed case alphabetic, digits, currency (international), arithmetic and punctuation characters (including period, comma, single quote, double quote and special characters)
Recognition technology to facilitate the processing of the MICR fonts of Cheques. Minimizes chances of error in clearing of Cheques. Easy and faster transfer of funds Provides a secure, high-speed method of scanning and processing information.
Automatically detects all barcodes on an image or a specific area within the image
Generates offline timesheets on a local server and uses the Import/Export module to synchronize with a central database.
This step allows users to manually correct extracted data that were not fully recognized correctly during auto recognition due to poor paper quality, poor legibility of fonts on paper, bad scan, color paper, etc.
This step allows users to manually index document by viewing the displayed image. This step may be used optionally when the recognition step is not utilized to extract index data automatically
This step allows users to review indexes that were manually entered by users in the Indexing step. This step is optional and may not be required.